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F. Firouzi and B. Farahani
• Device Management Layer – This layer is responsible for provisioning, registration, configuration, monitoring, control, and maintenance of connected IoT
devices.
• Data Ingestion Layer – This layer is the initial stop for data coming in from
different sources. Data is arranged and categorized here to enable data to move
smoothly into the other layers.
• Data Processing Layer – This layer focuses on processing the data collected in
the data ingestion layer. This is the first point where data analysis takes place as
data is transmitted to different destinations.
• Data Storage Layer – Storage can be challenging depending on the size of data
being collected. Utilizing a storage solution appropriate for large data size is
important, and this layer focuses on storing vast amounts of IoT data as efficiently
as possible. This layer includes different components such as data lake, data
warehouse, and databases.
• Application Layer – IoT application is a software consisting of Presentation
Tier/Layer (i.e., front-end), Business Logic Tier, Database Tier, as well as
Application Integration Tier (i.e., APIs and other interfaces) that manages IoT
devices, IoT data, users, and IoT services.
• Data Visualization and Reporting Layer – This layer is also known as a
presentation tier and is likely the most important layer because here is where
users can feel or see the value of the collected IoT data. It is important to grab
the user’s attention and make findings clearly understood.
• Orchestration Layer – IoT Cloud architecture often contains repeated processing
operations inside encapsulated workflows. These workflows convert source data
and transfer it among multiple sources or sinks. In addition, the management of
IoT Cloud is a very complex task that directly results from the sheer number of
virtual servers and application components. As the name of this layer suggests,
the orchestration layer consists of a set of tools to orchestrate the Cloud and other
layers.
4.2 Fundamentals of Cloud Computing
Cloud computing dates back to the 1950s and since then has evolved through
different technologies such as grid computing and large-scale mainframes. Cloud
computing has been defined by the National Institute of Standards and Technology
(NIST) as, “a model for enabling ubiquitous, convenient, on-demand network access
to a shared pool of configurable computing resources (e.g., networks, servers,
storage, applications, and services) that can be rapidly provisioned and released
with minimal management effort or service provider interaction.” The NIST also
suggests that Cloud computing consists of five basic characteristics, three models of
service, and four deployment models [2].
F. Firouzi and B. Farahani
• Device Management Layer – This layer is responsible for provisioning, registration, configuration, monitoring, control, and maintenance of connected IoT
devices.
• Data Ingestion Layer – This layer is the initial stop for data coming in from
different sources. Data is arranged and categorized here to enable data to move
smoothly into the other layers.
• Data Processing Layer – This layer focuses on processing the data collected in
the data ingestion layer. This is the first point where data analysis takes place as
data is transmitted to different destinations.
• Data Storage Layer – Storage can be challenging depending on the size of data
being collected. Utilizing a storage solution appropriate for large data size is
important, and this layer focuses on storing vast amounts of IoT data as efficiently
as possible. This layer includes different components such as data lake, data
warehouse, and databases.
• Application Layer – IoT application is a software consisting of Presentation
Tier/Layer (i.e., front-end), Business Logic Tier, Database Tier, as well as
Application Integration Tier (i.e., APIs and other interfaces) that manages IoT
devices, IoT data, users, and IoT services.
• Data Visualization and Reporting Layer – This layer is also known as a
presentation tier and is likely the most important layer because here is where
users can feel or see the value of the collected IoT data. It is important to grab
the user’s attention and make findings clearly understood.
• Orchestration Layer – IoT Cloud architecture often contains repeated processing
operations inside encapsulated workflows. These workflows convert source data
and transfer it among multiple sources or sinks. In addition, the management of
IoT Cloud is a very complex task that directly results from the sheer number of
virtual servers and application components. As the name of this layer suggests,
the orchestration layer consists of a set of tools to orchestrate the Cloud and other
layers.
4.2 Fundamentals of Cloud Computing
Cloud computing dates back to the 1950s and since then has evolved through
different technologies such as grid computing and large-scale mainframes. Cloud
computing has been defined by the National Institute of Standards and Technology
(NIST) as, “a model for enabling ubiquitous, convenient, on-demand network access
to a shared pool of configurable computing resources (e.g., networks, servers,
storage, applications, and services) that can be rapidly provisioned and released
with minimal management effort or service provider interaction.” The NIST also
suggests that Cloud computing consists of five basic characteristics, three models of
service, and four deployment models [2].